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Nick Travaglini
When an organization signs up for Honeycomb at the Enterprise account level, part of their support package is an assigned Technical Customer Success Manager. As one of these TCSMs, part of my responsibilities is helping a central observability team develop a strategy to help their colleagues learn how to make use of the product. At a minimum, this means making sure that they can log in, that relevant data is available, that they receive training on how to query, and perhaps that they collaborate with the rest of Honeycomb’s CS department to solve problems as they arise.
Michael Wilde
Incidents happen. What matters is how they’re handled. Most organizations have a strategy in place that starts with log searches—and logs/log searching are great, but log searching is also incredibly time consuming. Today, the goal is to get safer software out the door faster, and that means issues need to be discovered and resolved in the most efficient way possible.
Mike Terhar
The best mechanism to combat proliferation of uncontrolled resources is to use Infrastructure as Code (IaC) to create a common set of things that everyone can get comfortable using and referencing. This doesn’t block the ability to create ad hoc resources when desired—it’s about setting baselines that are available when people want answers to questions they’ve asked in the past.
Harrison Calato
George Miranda, Liz Fong-Jones, and Charity Majors, held a series of live discussions called the Authors’ Cut to bring core concepts of the book to life by applying them to real-world use cases. Now that the series is complete, we thought it would be helpful to combine all of the discussion recaps for your viewing pleasure. Each blog post below takes key concepts from chapters in the book and makes them more digestible.
George Miranda
In this post, we’re moving from the foundations of observability to things that become critical when you start practicing observability at scale. Tools like sampling and telemetry pipelines are useful at any size, but when your trickle of observability data suddenly becomes a torrential flood, these tools are essential.
Nick Rycar
As 2022 draws to a close, the Honeycomb team is getting ready to take some time to recharge our collective batteries and get ready for the new year. For some of us, that means spending some well-earned time away from our keyboards. For others, it means we get to spend our computer time doing something just for fun.
Martin Thwaites
In the last few years, the usage of databases that charge by request, query, or insert—rather than by provisioned compute infrastructure (e.g., CPU, RAM, etc.)—has grown significantly. They’re popular for a lot of the same reasons that serverless compute functions are, as the cost will scale with your usage. No one is using your site? No problem: you’re not charged.
Christine Yen
As long as humans have written software, we’ve needed to understand why our expectations (the logic we thought we wrote) don’t match reality (the logic being executed). To that end, we developed techniques to help measure reality—logging text strings, or capturing aggregated metrics—and persevered, seeking out newer and fancier logging or monitoring solutions over the intervening decades.
Liz Fong-Jones
You know that old adage about not seeing the forest for the trees? In our Authors’ Cut series, we’ve been looking at the trees that make up the observability forest—among them, CI/CD pipelines, Service Level Objectives, and the Core Analysis Loop. Today, I’d like to step back and take a look at how observability fits into the broader technical and cultural shifts in technology: cloud-native, DevOps, and SRE.
How do you solve the people and culture problems that are necessary in making the shift to adopt observability practices? And once you instill those changes, how do measure the benefits?
Phillip Carter
Learn how Jimdo, Upgrade, and Campspot benefited from OpenTelemetry, whether in improved performance, or by avoiding vendor lock-in.
Part of understanding a complex, distributed software system as a socio-technical system means taking seriously that the signals the stewards receive aren’t just chatter.
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Let’s dig into what we mean by an Availability Check and how that maps to observability, tracing, and supporting production systems.
Guest Blogger
You use NGINX as a proxy for your application, and you want to leverage Honeycomb’s amazing features to help make sense of the traffic data. Have no fear: Honeycomb has a solution just for you.
Just like any aspect of development, poor integration, invisible bottlenecks, and bugs can plague your CI/CD pipelines. And debugging them? Well, it’s complicated. To see what I mean, just fire up your favorite search engine to find content on “debugging CI/CD pipelines.” Look at all the different tools, studios, and blogs full of advice—it’s soul crushing.
Sasha Sharma
Someone once described dashboards to me as “expensive TV for software engineers.” At first, I stood there quietly shocked—dashboards had informed many root cause analyses (RCAs) in my life as a developer. Dashboards can be expensive TV—and sometimes even harmful false cocoons of safety (“Uh, p90 looks okay 🤷♀️!”) —but, approached instead with an analytical lens, they should be a pulse check for overall system health and a jumping-off point for investigations.
Observability is about understanding systems, which means more than just production. Moving from logs to tracing and showing causality can be done locally, as well. We can give developers the same superpowers that SREs have: observability-driven development.
Charity Majors
People use “observability team” as a catchall basket for all kinds of things these days—from cutting-edge tech to truly heinous hacks. Eh, it is what it is. The industry may be in a roiling state of massive flux, but I’m cautiously excited about the changes beginning to take shape and emerge from the muck. And I definitely think it’s worth spending some time talking about what observability teams can and should be.
One of the reasons that OpenTelemetry is great at doing this is that a lot of the common attributes you may find on a span are given standard names, so the systems receiving the data to visualize them don’t need to know the specifics of your system. This is really a superpower of OpenTelemetry, as it gives a level playing field for consumers of that information—meaning that you, as a developer, can forget about vendor-specific things.
David Marchante
By giving an overview into datasets, traces, and spans, you’ll get a peek behind the curtain into how Honeycomb facilitates observability in the hopes of arriving at a place where identifying the source of errors, finding performance problems, or understanding how data flows through a large system is made easier.
